Understanding how the brain works is arguably one of the greatest scientific challenges of our time. Although there have been piecemeal efforts to explain how different brain regions operate, no general theory of brain function is universally accepted. A fundamental underlying limitation is our ignorance of the brain's microcircuitry, the synaptic connections contained within any given brain area, which Cajal referred to as “impenetrable jungles where many investigators have lost themselves” (Ramón y Cajal, 1923). To explore these jungles, neuroscientists have traditionally relied on electrodes that sample brain activity only very sparsely—from one to a few neurons within a given region. However, neural circuits can involve millions of neurons, so it is probable that neuronal ensembles operate at a multineuronal level of organization, one that will be invisible from single neuron recordings, just as it would be pointless to view an HDTV program by looking just at one or a few pixels on a screen.

Neural circuit function is therefore likely to be emergent—that is, it could arise from complex interactions among constituents. This hypothesis is supported by the well-documented recurrent and distributed architecture of connections in the CNS. Indeed, individual neurons generally form synaptic contacts with thousands of other neurons. In distributed circuits, the larger the connectivity matrix, the greater the redundancy within the network and the less important each neuron is. Despite these anatomical facts, neurophysiological studies have gravitated toward detailed descriptions of the stable feature selectivity of individual neurons, a natural consequence of single-electrode recordings. However, given their distributed connections and their plasticity, neurons are likely to be subject to continuous, dynamic rearrangements, participating at different times in different active ensembles. Because of this, measuring emergent functional states, such as dynamical attractors, could be more useful for characterizing the functional properties of a circuit than recording receptive field responses from individual cells. Indeed, in some instances where large-scale population monitoring of neuronal ensembles has been possible, emergent circuit states have not been predictable from responses from individual cells.

Abstract: The notion of 'resilience' is rapidly emerging as a research topic in its own right, with the notion of 'social resilience' rapidly gaining importance. Yet, due to the relative novelty of the research field, discussions about processes of social resilience are not yet fully developed, especially with regard to how the inbuilt 'memory' of a local community helps shape resilience pathways (social memory). Interlinkages between social memory and community resilience are the focus of this study, with emphasis on analysis of the importance of rites, traditions and social learning processes for shaping community resilience/vulnerability.

Economics has typically been the social science of choice to inform public policy and policymakers. In the current paper we contemplate the role behavioral science can play i

On Amir (oamir@ucsd.edu), Dan Ariely, Alan Cooke, David Dunning, Nicholas Epley, Uri Gneezy, Botond Koszegi, Donald Lichtenstein, Nina Mazar, Sendhil Mullainathan (mullain@fas.harvard.edu), Drazen Prelec, Eldar Shafir and Jose Silva Marketing Letters, 2005, vol. 16, issue 3, 443-454 Abstract: Economics has typically been the social science of choice to inform public policy and policymakers. In the current paper we contemplate the role behavioral science can play in enlightening policymakers. In particular, we provide some examples of research that has and can be used to inform policy, reflect on the kind of behavioral science that is important for policy, and approaches for convincing policy-makers to listen to behavioral scientists. We suggest that policymakers are unlikely to invest the time translating behavioral research into its policy implications, and researchers interested in influencing public policy must therefore invest substantial effort, and direct that effort differently than in standard research practices. Copyright Springer Science + Business Media, Inc. 2005

Abstract: Our contemporary local and global communities face various forms of social issues. As a community psychologist, the author teaches college students in South Korea about the importance of context that shapes people's behaviors, under the title of Behavioral Economics in Our Community. In this presentation, the author wants to share what she learned from the students when they tried to apply the Behavioral Economics principles in the real communities. Students were required to identify one social issue per each to challenge in their communities and to propose an intervention program that nudges people to the desired direction. By paying attention to the social issues that need to be tackled to improve the individual and community well-being, students reflected on the Community Psychology principles. At the same time, by developing a feasible intervention program that borrows the Behavioral Economics principles, students learned how to make real changes in people?s behaviors. Specific examples of the students? successful projects will be shared in the presentation, including holding door for others, Korean spelling-check application for smartphones, and clean dumping of toilette paper. More importantly, the focus will be made on the process of each project as the students were also required to make a real contact with the person in charge, the person who can make decisions, the person who can influence the implementation of the project. In the presentation, therefore, the audience will learn about the contemporary South Korean socio-cultural environment as the context of Behavioral Economics application. https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fiises.net%2Fproceedings%2F34th-international-academic-conference-florence%2Ftable-of-content%2Fdetail%3Fcid%3D59%26iid%3D022%26rid%3D8099;h=repec:sek:iacpro:5908099

According to statisticbrain.com, one of the most popular new year’s resolution for 2017 was to make better financial decisions. However, in Peru, nearly 1.2 million (16 percent of all the financial consumers that hold a debt in the regulated financial system), people who have debt are reported to be late on their payments. This could have negative implications for their financial future making borrowing harder or more expensive. This raises the question: can debtors be nudged towards better financial well-being?

The US adversarial legal system and constitutional right to lobby Congress were designed with the assumption that citizens should have equal access to courts and legislators. Whatever one thinks of the legal profession, lawyers are the main powerbrokers to these systems. If we care about political equality, we have to care about which citizens and interests most lawyers are serving.

"As social media giants and Google face pressure to counter manipulation of their political content, the task is to temper a data-driven emphasis on customer engagement with social responsibility.

The day after the 2016 presidential election, Facebook CEO Mark Zuckerberg was asked whether social media had contributed to Donald Trump’s win. “A pretty crazy idea,” he responded at the time. But after months of internal sleuthing by media organizations, congressional investigations, and Facebook itself, the idea doesn’t look so far-fetched. “Calling that crazy was dismissive and I regret it,” Mr. Zuckerberg wrote in a Facebook post last week. “We will do our part to defend against nation states attempting to spread misinformation and subvert elections. We'll keep working to ensure the integrity of free and fair elections around the world, and to ensure our community is a platform for all ideas and force for good in democracy.” "

Computer-based swarm systems, aiming to replicate the flocking behavior of birds, were first introduced by Reynolds in 1987. In his initial work, Reynolds noted that while it was difficult to quantify the dynamics of the behavior from the model, observers of his model immediately recognized them as a representation of a natural flock. Considerable analysis has been conducted since then on quantifying the dynamics of flocking/swarming behavior. However, no systematic analysis has been conducted on human identification of swarming. In this paper, we assess subjects’ assessment of the behavior of a simplified version of Reynolds’ model. Factors that affect the identification of swarming are discussed and future applications of the resulting models are proposed. Differences in decision times for swarming-related questions asked during the study indicate that different brain mechanisms may be involved in different elements of the behavior assessment task. The relatively simple but finely tunable model used in this study provides a useful methodology for assessing individual human judgment of swarming behavior.

After many decades of flourishing computer science it is now rather evident that in a world dominated by different kinds of digital information, both applications and people are forced to seek new, innovative structures and forms of data management and organization. Following this blunt observation, researchers in informatics have strived over the recent years to tackle the non-unique and rather evolving notion of context, which aids significantly the data disambiguation process. Motivated by this environment, this work attempts to summarize and organize in a researcher-friendly tabular manner important or pioneer related research works deriving from diverse computational intelligence domains: Initially, we discuss the influence of context with respect to traditional low-level multimedia content analysis and search, and retrieval tasks and then we advance to the fields of overall computational context-awareness and the so-called human-generated contextual elements. In an effort to provide meaningful information to fellow researchers, this brief survey focuses on the impact of context in modern and popular computing undertakings of our era. More specifically, we focus to the presentation of a short review of visual context modeling methods, followed by the depiction of context-awareness in modern computing. Works dealing with the interpretation of context by human-generated interactions are also discussed herein, as the particular domain gains an ever-increasing proportion of related research nowadays. We then conclude the paper by providing a short discussion on (i) the motivation behind the included context type categorization into three main pillars; (ii) the findings and conclusions of the survey for each context category; and (iii) a couple of brief advices derived from the survey for both interested developers and fellow researchers.

The Evolution of Contextual Information Processing in InformaticsPhivos Mylonas

This course will help you become scientifically literate so that you can make better choices for yourself and the world. Unlike other courses on statistics and scientific methods, we explore global challenges - such as poverty or climate change - and then discuss how key approaches of statistics and scientific methods can help tackle these challenges. We present these approaches in a non-mathematical and easily accessible way. You will leave the course being able to recognize which efforts to do good in this world actually work, and you will have used your science literacy to make some personal changes in your life. Many current attempts to do good in this world are based on good intentions, but don’t work well, or are even harmful. In this course we talk to leading experts from academia, business and non-profit organizations about how we can use science to distinguish bad, good and even better ways of improving this world. We also invite you to change your own behavior to do more good. You will learn how to spot BS (bad science) in the media, how to evaluate whether a social program works or not, and how your career could have a better impact on this world. Finally, you will develop your own plan on how you are going to do good better with science.

The Cynefin framework is one of the leading sense-making tools for Management, built a foundation of complex adaptive systems theory. It provides a pragmatic means to recognise that different types of system require different leadership strategies. It is extensively used in the AGILE, LEAN and KANBAN communities and provides a means to bridge the gap between IT and both strategic and operational leadership. This one day seminar provides an opportunity to spend time with the originator of the Cynefin framework and gain an overview of the various methods and models used. It requires no previous experience but some basic reading will be provided in advance.

If targeting political extremes generates the most profit, then that's what these corporations will pursue. As many of you know, oftwominds.com was falsely labeled propaganda by the propaganda operation known as ProporNot back in 2016. The Washington Post saw fit to promote ProporNot's propaganda operation because it aligned with the newspaper's view that any site that wasn't pro-status quo was propaganda; the possibility of reasoned dissent has vanished into a void of warring accusations of propaganda and "fake news" --which is of course propaganda in action. Now we discover that profit-maximizing data-mining (i.e. Facebook and Google) can--gasp--be used for selling ideologies, narratives and candidates just like dog food and laundry detergent. The more extreme and fixed the views and the closer the groups are in size (i.e. the closer any electoral contest), the more profitable the corporate data-mining becomes.

Executive Summary Bad decisions can often be traced back to the way the decisions were made–the alternatives were not clearly defined, the right information was not collected, the costs and benefits were not accurately weighed. But sometimes the fault lies not in the decision-making process but rather in the mind of the decision maker. The way the human brain works can sabotage the choices we make. In this article, first published in 1998, John Hammond, Ralph Keeney, and Howard Raiffa examine eight psychological traps that can affect the way we make business decisions. The anchoring trap leads us to give disproportionate weight to the first information we receive. The status quo trap biases us toward maintaining the current situation–even when better alternatives exist. The sunk-cost trap inclines us to perpetuate the mistakes of the past. The confirming-evidence trap leads us to seek out information supporting an existing predilection and to discount opposing information. The framing trap occurs when we misstate a problem, undermining the entire decision-making process. The overconfidence trap makes us overestimate the accuracy of our forecasts. The prudence trap leads us to be overcautious when we make estimates about uncertain events. And the recallability trap prompts us to give undue weight to recent, dramatic events. The best way to avoid all the traps is awareness–forewarned is forearmed. But executives can also take other simple steps to protect themselves and their organizations from these mental lapses. The authors describe what managers can do to ensure that their important business decisions are sound and reliable.

Intelligent people are better at cooperating with others, new research finds. While personality traits like being generous and conscientious have an effect on cooperation, higher IQ is the main factor that encourages people to work well together. That is why people with high IQs are so essential: without them society would not work. People with lower intelligence tend not to use a consistent strategy and fail to consider the consequences of their actions, the researchers also found.

IAbstract: Virtual community was designed to organise different communities and getting people involved in creating and sharing knowledge. It was also called e-information exchange system. Bock et al. argued that the research perspectives of knowledge sharing should be classified into economics, social psychology and sociology perspectives. We present a conceptual framework based on economic, social psychology and social ecology perspective and propose a set of propositions for knowledge sharing in virtual community. Finally, we introduce punctuated equilibrium as third theoretical perspective to understand whether the factors affecting knowledge sharing may change with time.

Highlighting and breaking down the 12 most useful and universal mental models that will make you smarter and more productive.

12 Ways to Get Smarter in One Infographic View the high resolution version of today’s graphic by clicking here. The level of a person’s raw intelligence, as measured by aptitude tests such as IQ scores, is generally pretty stable for most people during adulthood. While it’s true that there are things you can do to fine tune your natural capabilities, such as doing brain exercises, puzzle solving, and getting optimal sleep – the amount of raw brainpower you have is difficult to increase in any meaningful or permanent way. For those of us who constantly strive to be high-performers in our fields, this seems like bad news. If we can’t increase our processing power, then how can we solve life’s bigger problems as we move up the ladder? THE KEY IS MENTAL MODELS The good news is that while raw cognitive abilities matter, it’s how you use and harness those abilities that really makes the difference. The world’s most successful people, from Ray Dalio to Warren Buffett, are not necessarily leagues above the rest of us in raw intelligence – they have simply developed and applied better mental models of how the world works, and they use these principles to filter their thoughts, decisions, strategies, and execution. Today’s infographic comes from best-selling author and entrepreneur Michael Simmons, who has collected over 650 mental models through his work. The infographic, in a similar style to one we previously published on cognitive biases, synthesizes these models down to the most useful and universal mental models that people should learn to master first.

Here's all 188 cognitive biases in existence, grouped by how they impact our thoughts and actions. We also give some specific cognitive bias examples.

Every Single Cognitive Bias in One Infographic View the high resolution version of today’s graphic by clicking here. The human brain is capable of incredible things, but it’s also extremely flawed at times. Science has shown that we tend to make all sorts of mental mistakes, called “cognitive biases”, that can affect both our thinking and actions. These biases can lead to us extrapolating information from the wrong sources, seeking to confirm existing beliefs, or failing to remember events the way they actually happened! To be sure, this is all part of being human – but such cognitive biases can also have a profound effect on our endeavors, investments, and life in general. For this reason, today’s infographic from DesignHacks.co is particularly handy. It shows and groups each of the 188 known confirmation biases in existence.

An important way to resolve games of conflict (snowdrift, hawk–dove, chicken) involves adopting a convention: a correlated equilibrium that avoids any conflict between aggressive strategies. Dynamic networks allow individuals to resolve conflict via their network connections rather than changing their strategy. Exploring how behavioural strategies coevolve with social networks reveals new dynamics that can help explain the origins and robustness of conventions. Here, we model the emergence of conventions as correlated equilibria in dynamic networks. Our results show that networks have the tendency to break the symmetry between the two conventional solutions in a strongly biased way. Rather than the correlated equilibrium associated with ownership norms (play aggressive at home, not away), we usually see the opposite host–guest norm (play aggressive away, not at home) evolve on dynamic networks, a phenomenon common to human interaction. We also show that learning to avoid conflict can produce realistic network structures in a way different than preferential attachment models.

In the past weeks, I have received several requests to address the merits of the Anna D. Broido and Aaron Clauset (BC) preprint [1] and their fruitless search for scale-free networks in nature. The preprint’s central claim is deceptively simple: It starts from the textbook definition of a scale-free network as a network with a power law in the degree distribution [2]. It then proceeds to fit a power law to 927 networks, finding that only 4% are scale-free. The author's conclusion that ‘scale-free networks are rare,’ is turned into the title of the preprint, helping it to get maximal attention. It worked—Quanta magazine accepted its conclusions without reservations. AfterThe Atlantic carried the article, the un-refereed preprint received a degree of media exposure that the original discovery of scale-free networks never enjoyed.

While I saw the conceptual problems with the manuscript, I was convinced that the paper must be technically proficient. Yet, once I did dig into it, it was a real ride. If you have the patience to get to the end of this commentary, you will see where it fails at the conceptual level. But, we will learn that it also fails, repeatedly, at the technical level.

Love is All You NeedClauset's fruitless search for scale-free networks

Solutions are only possible outside these ossified, self-serving centralized hierarchies. Correspondent Dan F. asked me to reprint some posts on solutions to the systemic problems I've outlined for years, most recently in How Much Longer Can We Get Away With It? and Checking In on the Four Intersecting Cycles. I appreciate the request, because it's all too easy to dwell on what's broken rather than on the difficult task of fixing what's broken. I've laid out a variety of solutions to structural problems in my many books, and I'll attempt a brief synthesis in this post.

I have been re-reading the work of Prof Paul Cilliers, who truly was a pioneer in complexity thinking. I came across this summary of the general characteristcs of complex systems in a piece he wrote in 2000. It is concise and accessible qualitative description of complexity and I thought it would be useful to share here on my blog.

Recent research on the network modeling of complex systems has led to a convenient representation of numerous natural, social, and engineered systems that are now recognized as networks of interacting parts. Such systems can exhibit a wealth of phenomena that not only cannot be anticipated from merely examining their parts, as per the textbook definition of complexity, but also challenge intuition even when considered in the context of what is now known in network science. Here, we review the recent literature on two major classes of such phenomena that have far-reaching implications: (a) antagonistic responses to changes of states or parameters and (b) coexistence of seemingly incongruous behaviors or properties—both deriving from the collective and inherently decentralized nature of the dynamics. They include effects as diverse as negative compressibility in engineered materials, rescue interactions in biological networks, negative resistance in fluid networks, and the Braess paradox occurring across transport and supply networks. They also include remote synchronization, chimera states, and the converse of symmetry breaking in brain, power-grid, and oscillator networks as well as remote control in biological and bioinspired systems. By offering a unified view of these various scenarios, we suggest that they are representative of a yet broader class of unprecedented network phenomena that ought to be revealed and explained by future research.

A survey on the use of data science techniques in local government run by the Oxford Internet Institute

Welcome to the Data Science for Local Government Survey! The aim of this short survey is to understand more about both the data sources and the analytical techniques that local governments use to inform policy and deliver services. We are particularly interested in the growing use of new data sources (such as open data, internet of things data and social media) and novel approaches to policy implementation and analysis (such as the use of experiments and machine learning), a joint change which some are labelling the emergence of “data science”. We are interested in measuring the spread of this type of data science within local governments in Europe.

Most executives think of decision making as a singular event that occurs at a particular point in time. In reality, though, decision making is a process fraught with power plays, politics, personal nuances, and institutional history. Leaders who recognize this make far better decisions than those who persevere in the fantasy that decisions are events they alone control. That said, some decision-making processes are far more effective than others. Most often, participants use an advocacy process, possibly the least productive way to get things done. They view decision making as a contest, arguing passionately for their preferred solutions, presenting information selectively, withholding relevant conflicting data so they can make a convincing case, and standing firm against opposition. Much more powerful is an inquiry process, in which people consider a variety of options and work together to discover the best solution. Moving from advocacy to inquiry requires careful attention to three critical factors: fostering constructive, rather than personal, conflict; making sure everyone knows that their viewpoints are given serious consideration even if they are not ultimately accepted; and knowing when to bring deliberations to a close. The authors discuss in detail strategies for moving from an advocacy to an inquiry process, as well as for fostering productive conflict, true consideration, and timely closure. And they offer a framework for assessing the effectiveness of your process while you’re still in the middle of it. Decision making is a job that lies at the very heart of leadership and one that requires a genius for balance: the ability to embrace the divergence that may characterize early discussions and to forge the unity needed for effective implementation.

Sharing your scoops to your social media accounts is a must to distribute your curated content. Not only will it drive traffic and leads through your content, but it will help show your expertise with your followers.

Integrating your curated content to your website or blog will allow you to increase your website visitors’ engagement, boost SEO and acquire new visitors. By redirecting your social media traffic to your website, Scoop.it will also help you generate more qualified traffic and leads from your curation work.

Distributing your curated content through a newsletter is a great way to nurture and engage your email subscribers will developing your traffic and visibility.
Creating engaging newsletters with your curated content is really easy.